Wave position division and user grouping method, device, equipment and medium

Abstract

The application discloses a wave position division and user grouping method, device, equipment and medium, the method comprises the following steps: in order to maximize the total transmission rate of wave position, and reduce the total number of divided user groups to reduce the transmission delay of system, an optimization target is established, the user distribution density is determined by using an adjacency matrix, the wave position is divided from the high-density area, and the wave position center is continuously adjusted to optimize the objective function, the problem is decomposed into successive solving existing optimal, until the end condition is reached, the wave position center is adjusted to optimize the transmission rate, the performance of the system in the aspects of throughput and average waiting time is improved, the existing optimal is solved successively, until the end condition is reached, the number of iterations is reduced, and the operation efficiency is improved.

Description

Technical Field

[0001] This invention belongs to the field of satellite communication technology and relates to a method, apparatus, device and medium for wavelet partitioning and user grouping. Background Technology

[0002] Large-scale low-Earth orbit (LEO) satellite constellations, with their advantages of wide coverage, low latency, and flexible deployment, can provide seamless, 24 / 7 global service, attracting significant attention from the communications industry. In traditional multi-beam satellite systems, each beam is allocated fixed power and frequency resources. However, this is insufficient to handle the uneven distribution, diverse, and time-varying service requests from ground terminals, leading to decreased system resource utilization. Therefore, how to utilize limited onboard resources to address complex service needs has become a hot topic for researchers. Against this backdrop, beam hopping technology has emerged. It aims to achieve coverage and service across regions with fewer beams through flexible hopping, allocating resources more rationally and effectively. The basic idea of ​​beam hopping is to utilize time-division multiplexing to divide the service cycle of a beam into multiple time slots. A certain number of beams are scheduled to illuminate positions within each time slot. By changing the pointing and beamwidth, hopping between beam positions is achieved, thereby supporting user services under different beam positions and improving resource utilization efficiency.

[0003] Before beam scheduling, it is necessary to first divide the satellite service area and users, plan the beam positions, and then allocate the time slots and other resources of the beam positions. The beam positions are then selectively lit according to the time slots to provide services. In fact, the beam position division results not only affect the beam time slot allocation and lighting situation, but also affect the service quality of users and the performance of the system.

[0004] Current literature on wavelet partitioning schemes mainly includes: fixed wavelet partitioning, which uses wavelets of fixed size for dense service areas; iterative algorithms to group users to achieve wavelet partitioning, such as wavelet partitioning methods based on mean-based algorithms and wavelet partitioning methods based on center-based algorithms; and grouping schemes based on wavelet radius levels, which are improvements on fixed wavelet partitioning by classifying wavelet sizes, setting wavelet radius widths to a fixed number of values, and merging or splitting wavelets according to optimization objectives.

[0005] However, using a fixed-size, densely packed satellite service area ignores the impact of the relative positional relationship between the beam center and users within the beam on beam scheduling and system performance. This can lead to users being distributed at the beam edge, with a large number of beams waiting for service, resulting in suboptimal user channel quality and significant system latency. While beam grouping methods, such as those based on center-based algorithms, can be implemented through extensive iterative calculations, their results are highly dependent on the initial point selection and involve high computational complexity. Beam level classification, based on fixed beam division, still fails to flexibly consider the impact of the relative positional relationship between the beam center and users within the beam on system performance.

[0006] To address the aforementioned issues, it is necessary to comprehensively consider the relative relationship between users and satellites in highly mobile low-Earth orbit satellite hopping beam systems and dynamically allocate beam positions accordingly, thereby improving system performance.

[0007] Based on the aforementioned technical problems in the existing technology, this invention proposes a method, apparatus, device, and medium for wave position division and user grouping. Summary of the Invention

[0008] The purpose of this invention is to address the shortcomings of existing technologies by proposing a method, apparatus, device, and medium for beam-slot allocation and user grouping, thereby solving the problems of user grouping and beam-hopping beam-slot allocation when the distribution of users under satellite is random and the service demand is uneven.

[0009] The present invention adopts the following technical solution:

[0010] In a first aspect, the present invention provides a method for wave position partitioning and user grouping, comprising:

[0011] Step 1: In a region on the Earth's surface, based on user access information, obtain the current set of serving satellites for that region, the user set U under each satellite, its geographical location distribution, and channel information. Each satellite can generate a maximum of N in each time slot. b A directional beam;

[0012] Step 2: Assume there is an s-th satellite, and the total number of users served by the s-th satellite is N. u , u(1≤u≤N u The latitude and longitude coordinates of the users are ω u Based on the radiation characteristics of the antennas mounted on the satellite, the radius constraint R for dividing user groups is obtained. b ;

[0013] Step 3: With the goal of maximizing the total transmission rate of the wavelet and reducing the total number of user groups to reduce the transmission delay of the system, and with the constraints of the radius distance of the wavelet and each user belonging to one group, and the termination condition of all users being divided, an optimization problem is established.

[0014] Step 4: For the optimization problem, density clustering is used to obtain the density of user distribution for ungrouped users based on user distribution density. The wave positions of users to be divided are sorted according to the density to obtain the adjacency matrix G of the users at the sub-star point.

[0015] Step 5: Based on the adjacency matrix G, start partitioning from the user with the highest number of adjacent users one by one. During the partitioning process, solve the problem with the goal of maximizing the transmission rate of the current group to obtain the mapping relationship between users and groups and the location information of the groups, until all users have been partitioned.

[0016] Furthermore, in step 3, for the already divided i-th user group set m i Total transmission rate of the packet set Given the sum of the transmission rates of all users within the wavelength range, we have:

[0017]

[0018] Among them, C u The information transmission rate of the u-th user within the wavelength range is obtained from Shannon's formula:

[0019]

[0020] Where B is the system bandwidth, n0 is the noise power, and P u This represents the received power of user u.

[0021] Furthermore, in step 3, each user belongs to a wavelength position and is served by the same beam, establishing the relationship between the user set within a wavelength position and the total user set:

[0022]

[0023]

[0024] The optimization problem aims to maximize the total transmission rate of the wavelength and reduce the total number of user groups to lower the system's transmission delay. It is constrained by the radius distance of the wavelength and the condition that each user belongs to only one group. The problem terminates when all users have been divided. It is an empty set.

[0025] Furthermore, in step 3, the optimization problem is expressed as:

[0026]

[0027]

[0028] Where, N mm is the total number of user groups. i Let ω be the set of users in the i-th group. u Let Ω be the latitude and longitude coordinates of the u-th user. i Let d(ω) be the center latitude and longitude coordinates of the i-th user group. u ,Ω i () represents the distance between two latitude and longitude coordinates.

[0029] Furthermore, step 4 includes:

[0030] Step 4.1: Based on the geographic location information of the users under the satellite and the radius constraint settings, calculate the adjacency relationship between users to obtain the adjacency matrix G of the users under the satellite.

[0031] Step 4.2: Calculate the number of neighboring users for each user based on the adjacency matrix G;

[0032] Step 4.3: Sort by the number of adjacent users. Users with a large number of adjacent users are in the high-density area, and vice versa.

[0033] Furthermore, step 5 includes:

[0034] Step 5.1: Sort each user by the number of their neighbors from highest to lowest, record the set of users U′ with the most neighbors, and record the number of the most neighbors at this time as p;

[0035] Step 5.2, for user u∈U′, obtain the users who can be assigned to the same group, where the users in the same group are those whose distance from u is less than R. b For users, the user grouping result m is obtained, and the latitude and longitude coordinates of the group center are Ω = ω. u Calculate the total transmission rate of the current group and record it as a temporary variable C. max :

[0036] C max =∑ u∈m C u ;

[0037] Step 5.3: Update the group center to the latitude and longitude center Ω′ of all users within the group, re-obtain the users within the group based on Ω′, calculate the current total transmission rate C′ of the group, and compare C′ with the coordinates of all users within the group. max Given the total transmission rate C′, retain the wavelet partitioning result with the larger transmission rate value from the two partitionings, and update C. max ;

[0038] Step 5.4, repeat step 5.3 until the group division result remains unchanged, then the group division is complete. Remove the divided users from sets U and U′, update the adjacency matrix G, and delete the adjacency relationship between the divided users and the undivided users.

[0039] Step 5.5: Continue to repeat steps 5.2 to 5.4 for users in user set U′ until all users in U′ have been partitioned.

[0040] Secondly, the present invention provides an apparatus for wave position division and user grouping, comprising:

[0041] The user access and information statistics module is used for user access and information statistics. The satellite obtains user information through the user access and information statistics module.

[0042] The wave position formation and user grouping calculation module is used for wave position partitioning and user grouping methods based on density clustering, to optimize the wave position partitioning process, obtain the mapping relationship between users and wave positions, and the geographical location information of wave positions;

[0043] The beam scheduling and transmission module selects the current beam position from the candidate set based on the beam position and projects the beam to achieve data transmission.

[0044] Thirdly, the present invention provides an electronic device including one or more processors and one or more memories, wherein the one or more memories store at least one computer program, the computer program being loaded and executed by the one or more processors to implement the operations performed by the wavelet partitioning and user grouping method.

[0045] Fourthly, the present invention provides a computer-readable storage medium storing at least one computer program, which is loaded and executed by a processor to implement the operations performed by the wavelet partitioning and user grouping method.

[0046] The beneficial effects of this invention are:

[0047] The wavelet partitioning and user grouping method, system, device and medium described in this invention successively adjust the wavelet center to optimize the transmission rate, thereby improving the system's performance in terms of throughput and average waiting time.

[0048] Starting from a high-density region and solving for existing optimal solutions one by one until the termination condition is met, the number of iterations is reduced and the running efficiency is improved.

[0049] Considering the uncertainty of the number of wave positions, density clustering is adopted to divide the wave positions starting from high-density regions. Compared with iterative algorithms, this reduces the impact of the randomness of the partition selection on system performance and algorithm operation. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of beam skipping and wave position division in an embodiment of the present invention;

[0051] Figure 2 This is a flowchart illustrating the beam hopping system beam assignment and user grouping method in an embodiment of the present invention.

[0052] Figure 3 This is a flowchart illustrating the process of determining user distribution density in an embodiment of the present invention.

[0053] Figure 4 This is a flowchart illustrating the waveform partitioning algorithm in an embodiment of the present invention.

[0054] Figure 5 This is a comparison chart of the average throughput of the method described in the embodiments of the present invention with that of fixed wavelet partitioning and wavelet partitioning scheme based on p-center algorithm;

[0055] Figure 6 The above is a comparison chart of SINR CDF between the method described in the embodiments of the present invention, fixed wavelet partitioning, and wavelet partitioning scheme based on p-center algorithm;

[0056] Figure 7 This is a comparison chart of the average waiting time of the method described in the embodiments of the present invention with that of fixed wave position partitioning and wave position partitioning scheme based on p-center algorithm;

[0057] Figure 8 This is a comparison chart of user satisfaction with the method described in the embodiments of the present invention, fixed wave position partitioning, and wave position partitioning scheme based on the p-center algorithm;

[0058] Figure 9 This is a schematic diagram of a wave position division device provided in an embodiment of the present invention.

[0059] In the diagram, 100 represents the user access and information statistics module, 200 represents the beamforming and user grouping calculation module, and 300 represents the beam scheduling and transmission module. Detailed Implementation

[0060] To better understand the above-mentioned objectives, features and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, unless otherwise specified, the embodiments and features in the embodiments of this application can be combined with each other.

[0061] Example

[0062] With the development of large-scale satellite constellation communication systems, traditional multi-beam technology is struggling to cope with the uneven distribution, diverse, and time-varying service requests from ground terminals, leading to decreased system resource utilization. Therefore, beam hopping technology has emerged, aiming to achieve coverage and service across a region using fewer beams in a flexible hopping manner, thus allocating resources more rationally and effectively. The basic idea of ​​beam hopping is to utilize time division multiplexing to divide the service period of a beam into multiple time slots, scheduling a certain number of beams in each time slot. By changing the pointing and beamwidth, beam positions are illuminated, thereby supporting user services under different beam positions and improving resource utilization efficiency. However, in beam hopping systems, it is necessary to perform beam position allocation and user grouping for satellite service users to support the design of subsequent beam hopping. Therefore, this application provides a beam position allocation and user grouping method, system, device, and medium to solve the above problems.

[0063] like Figure 1 As shown, satellite 1 and satellite 2 are used as examples to represent satellites that emit beams to serve users, and the satellite 1 wave position and satellite 2 wave position are used as examples to represent the wave positions that the satellite can schedule. It should be noted that satellite 1 and satellite 2 each use multiple beams, and at the same time, each beam is only scheduled to one wave position.

[0064] The proposed wavelet partitioning and user grouping method takes into account the uncertainty of the number of wavelets to be partitioned. First, it aims to maximize the total transmission rate of the wavelets and reduce the total number of user groups to reduce the transmission delay of the system. An optimization objective is established, the user distribution density is determined by using the adjacency matrix, the wavelets are partitioned starting from the high-density area, and the wavelet center is continuously adjusted to optimize the objective function. The problem is decomposed into solving the existing optimal solution one by one until the termination condition is reached.

[0065] Specifically, such as Figure 2 As shown, the execution of the method on the satellite side includes:

[0066] S01. Deploy a low-Earth orbit satellite constellation hop-beam communication scenario, set the user distribution method, and deploy points across the Earth. Select a specific area on the sphere for investigation, adopt a proximity access strategy, and obtain the current set of serving satellites for that area, as well as the user set U under each satellite, its geographical location distribution, and channel information based on user access status. Use a phased array antenna to generate a maximum of N in each time slot. b A directional beam provides services to users in a flexible and variable hopping beam configuration;

[0067] S02. For the s-th satellite, the total number of service users is N. u , u(1≤u≤N u The latitude and longitude coordinates of the users are ω uBased on the radiation characteristics of the phased array antenna onboard the satellite, the 3dB gain angle was calculated. Using this angle and the satellite's altitude information, the radius constraint R for dividing the waveband was then calculated. b ;

[0068] S03. Establish a problem model, targeting the i-th user group set m that has been divided. i The total transmission rate of this packet This is the sum of the transmission rates of all users within the wavelength range, i.e.:

[0069]

[0070] Among them, C u The information transmission rate of the u-th user within the wavelength range is obtained from Shannon's formula:

[0071]

[0072] Where B is the system bandwidth, n0 is the noise power, and P u For the received power of user u, it should be noted that P u It is related to the satellite antenna transmitting antenna gain, the user receiving antenna gain, transmission loss, and frequency band;

[0073] Considering that each user belongs to only one wavelength and is served by the same beam, establish the relationship between the set of users within a wavelength and the total set of users:

[0074]

[0075]

[0076] Therefore, with the objectives of maximizing the total transmission rate of the wavelets and minimizing the total number of user groups to reduce system transmission delay, and with constraints such as the radius distance of the wavelets and each user belonging to only one group, and with the termination condition that all users have been divided, the following optimization problem is established:

[0077]

[0078]

[0079] Where, N m m is the total number of user groups. i Let ω be the set of users in the i-th group. u Let Ω be the latitude and longitude coordinates of the u-th user. i Let d(ω) be the center latitude and longitude coordinates of the i-th user group. u ,Ω i This represents the distance between these two latitude and longitude coordinates. It is an empty set;

[0080] S04. Regarding the optimization problem described in S03, due to the uneven distribution of users, the total number of groups cannot be determined solely based on user geographic location information and wave radius. Therefore, using the idea of ​​density clustering, based on the user distribution density, the density of user distribution is obtained for users who have not been grouped, and the order of users to be divided is sorted according to the density.

[0081] S05. Based on the adjacency matrix G, start dividing the region with high user density one by one, and solve the problem with the goal of maximizing the transmission rate of the current group during the division process to obtain the mapping relationship between users and groups and the location information of the groups, until all users have been divided.

[0082] In the above embodiment, the wave position can be assumed to be circular, and the radius of each wave position under the satellite is the same. Then the subsequent division constraints can be based on the radius.

[0083] It should be noted that the wave position will be deformed due to its location at the edge of satellite service. Each wave position has its specific radius. In this case, the subsequent subdivision can be obtained by considering the relationship between the center position of the wave position and the satellite position, with a 3dB gain angle as a constraint.

[0084] In S01 of the above embodiment, considering the low-Earth orbit satellite constellation hopping beam communication scenario, the satellite constellation is constructed with a certain number of orbits, number of satellites per orbit, and phase factor. The satellites are equipped with phased array antennas to achieve beam projection and flexible pointing, thereby deploying a satellite constellation for the hopping beam scenario. Meanwhile, users are distributed on Earth.

[0085] like Figure 3 As shown, S04 includes:

[0086] S401, obtain the adjacency matrix G of the users under the star, and calculate the adjacency relationship between users based on the geographical location information of the users under the star and the radius constraint settings;

[0087] S402, calculate the number of neighboring users for each user based on the adjacency matrix G;

[0088] S403 sorts users based on the number of adjacent users. Users with a large number of adjacent users are in high-density areas, and vice versa.

[0089] like Figure 4 As shown, S05 includes:

[0090] S501, calculate the maximum number of adjacent users p and the user set U′ that can be grouped in this case based on the adjacency matrix G, record the user set U′ with the maximum number of adjacent users in the current case, and record the maximum number of adjacent users p at this time.

[0091] S502, calculate the initial partitioning results and transmission rate. For user u∈U′, first obtain the users who can be assigned to the same group as u, i.e., those whose distance to u is less than R. b For users, the user grouping result m is obtained, and the latitude and longitude coordinates of the group center are Ω = ω. u Furthermore, calculate the total transmission rate of the current group and record it as a temporary variable C. max :

[0092] C max =∑ u∈m C u ;

[0093] S503, continue updating from the group obtained in S502, updating the group center to the latitude and longitude center Ω′ of all users in the group, re-obtaining the users in the group based on this center, calculating the current total transmission rate C′ of the group, and comparing C′ with the data obtained in S502. max Compared with the total transmission rate C′, the wavelet allocation result with the larger midpoint is retained, and C is updated. max ;

[0094] S504, repeat S503 until the group division result remains unchanged, then the group division is complete. Remove the divided users from sets U and U′, update the adjacency matrix G, and delete the adjacency relationship between divided users and undivided users to prevent the same user from being divided into different groups.

[0095] S505, continue to repeat S502 to S504 for users in user set U′, until all users in U′ have been divided;

[0096] S506, update p = p-1, repeat S501, based on the new p value, the ungrouped user set U, and the adjacency matrix G of the deleted users, obtain the user set U′ with the number of adjacent users p, repeat S502 to S504 until the users in U′ are divided.

[0097] S507, repeat S506, until... In other words, all users have been divided, the mapping relationship between groups and users has been obtained, as well as the center latitude and longitude coordinates of each group, and the results of wave position division and user grouping have been obtained;

[0098] To verify the superior technical effect of the proposed wave position partitioning and user grouping method, the method was compared with a fixed wave position partitioning method and a wave position partitioning method based on the p-center algorithm, and corresponding simulation results were obtained, such as... Figure 5 , Figure 6 , Figure 7 , Figure 8As shown, the fixed beam position division method refers to the beam positions being densely distributed in the investigation area, while the beam position division method based on the p-center algorithm refers to the beam position division result obtained by successively increasing the p value and simultaneously dividing p beam positions using the p-center algorithm. Simulation results show that the method can improve the throughput performance of the system while ensuring low computational complexity. Therefore, the method described in this embodiment can improve the resource utilization rate of the low-orbit satellite hopping beam system while saving computational resources.

[0099] like Figure 9 As shown, the wave position division and user grouping device includes:

[0100] The user access and information statistics module 100 is used for user access and information statistics. The satellite can obtain user information, including geographical location information, channel conditions, etc., through the user access and information statistics module 100.

[0101] The wave position formation and user grouping calculation module 200 is used to implement the wave position division and user grouping method. It applies a density clustering-based wave position division and user grouping method to optimize the wave position division process and obtain the mapping relationship between users and wave positions as well as the geographical location information of the wave positions.

[0102] The beam scheduling and transmission module 300 selects the scheduled beam position from the candidate set based on the formed beam position and projects the beam to realize data transmission.

[0103] In the above embodiments, the beam scheduling and transmission module 300 can be used to: obtain a candidate set of beam projection positions by using the mapping relationship between users and beam positions and the geographical location relationship of beam positions obtained by the beam position forming and user grouping module 200. At each time, the beam selects a beam position from the candidate set and projects it. The same beam can only project the same beam position at the same time.

[0104] The electronic device includes:

[0105] Memory, used to store executable instructions;

[0106] The processor is used to read and execute executable instructions stored in memory to perform bit partitioning and user grouping.

[0107] The computer-readable storage medium includes:

[0108] The device stores a computer program that, when executed by a processor, enables the processor to perform wavelet partitioning and user grouping methods.

[0109] This invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the invention as claimed. The scope of protection of this invention is defined by the appended claims.

Claims

1. A method for wave position partitioning and user grouping, characterized in that, include: Step 1: In a region on the Earth's surface, based on user access information, obtain the current set of serving satellites for that region and the set of users under each satellite. With its geographical location distribution and channel information, each satellite can generate a maximum of [data / capacity] per time slot. A directional beam; Step 2, assume there exists a first... The first satellite, the The total number of satellite service users is , No. The latitude and longitude coordinates of each user are in, Based on the radiation characteristics of the antennas on board the satellite, the radius constraints for dividing user groups are obtained. ; Step 3: With the goal of maximizing the total transmission rate of the wavelet and reducing the total number of user groups to reduce the transmission delay of the system, and with the constraints of the radius distance of the wavelet and each user belonging to one group, and the termination condition of all users being divided, an optimization problem is established. Step 4: For the optimization problem, density clustering is used. Based on the user distribution density, the density of the user distribution is obtained for ungrouped users. The wave positions of the users to be divided are sorted according to the density to obtain the adjacency matrix of the users at the sub-star point. ; Step 5, based on the adjacency matrix The algorithm starts by dividing users into groups one by one, starting with the user with the highest number of adjacent users. During the division process, the algorithm aims to maximize the transmission rate of the current group to obtain the mapping relationship between users and groups, as well as the location information of the groups, until all users have been divided.

2. The wave position division and user grouping method according to claim 1, characterized in that, In step 3, for the already divided... User group set Total transmission rate of the packet set This is the sum of the transmission rates of all users within the wavelength range, i.e.: ； in, For the first wave position The information transmission rate per user is obtained using Shannon's formula: ； in, For system bandwidth, For noise power, For users The received power.

3. The wave position division and user grouping method according to claim 2, characterized in that, In step 3, each user belongs to a wavelength position and is served by the same beam. The relationship between the user set within a wavelength position and the total user set is established: ； ； The optimization problem aims to maximize the total transmission rate of the wavelength and reduce the total number of user groups to lower the system's transmission delay. It is constrained by the radius distance of the wavelength and the condition that each user belongs to only one group. The problem terminates when all users have been divided. It is an empty set.

4. The wave position division and user grouping method according to claim 3, characterized in that, In step 3, the optimization problem is expressed as: ； ； in, The total number of user groups. For the first A collection of users in a group. For the first Latitude and longitude coordinates of each user For the first The center latitude and longitude coordinates of each user group It represents the distance between two latitude and longitude coordinates.

5. The wave position partitioning and user grouping method according to claim 4, characterized in that, Step 4 includes: Step 4.1: Based on the geographic location information of the users under the satellite and the radius constraint settings, calculate the adjacency relationship between users to obtain the adjacency matrix of the users under the satellite. ; Step 4.2, based on the adjacency matrix Calculate the number of neighboring users for each user; Step 4.3: Sort by the number of adjacent users. Users with a large number of adjacent users are in the high-density area, and vice versa.

6. The wave position division and user grouping method according to claim 4, characterized in that, Step 5 includes: Step 5.1: Sort users from highest to lowest number of neighbors and record the set of users with the most neighbors. And record the maximum number of adjacent users at this time. ; Step 5.2, for the user Users can be assigned to the same group of users, where users in the same group are... The distance is less than Users who received the user grouping results At this time, the latitude and longitude coordinates of the group's center Calculate the total transmission rate of the current group and record it as a temporary variable. : ； Step 5.3: Update the group center to the latitude and longitude centers of all users in the group. ,according to Reacquire users within the group and calculate the total transmission rate of the current group. ,Compare With total transmission rate Retain the wavelet partitioning result with the larger transmission rate value from these two partitionings, and update... ; Step 5.4: Repeat step 5.3 until the group partitioning result remains unchanged. The group partitioning is then complete. Remove the partitioned users from the set. and Remove and update the adjacency matrix. Delete the adjacent relationships between users who have been assigned to a user group and users who have not been assigned to a user group; Step 5.5, continue with the user set For users in the process, repeat steps 5.2 to 5.4 until... All users have been assigned.

7. An apparatus for use in the wave position division and user grouping method according to any one of claims 1-6, characterized in that, include: The user access and information statistics module is used for user access and information statistics. The satellite obtains user information through the user access and information statistics module. The wave position formation and user grouping calculation module is used for wave position partitioning and user grouping methods based on density clustering, to optimize the wave position partitioning process, obtain the mapping relationship between users and wave positions, and the geographical location information of wave positions; The beam scheduling and transmission module selects the current beam position from the candidate set based on the beam position and projects the beam to achieve data transmission.

8. An electronic device, characterized in that, It includes one or more processors and one or more memories, wherein the one or more memories store at least one computer program, which is loaded and executed by the one or more processors to perform the operations performed by the wavelet partitioning and user grouping method as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one computer program, which is loaded and executed by a processor to perform the operations performed by the wavelet partitioning and user grouping method as described in any one of claims 1-6.

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